Arch Sex Behav DOI 10.1007/s10508-015-0572-7
ORIGINAL PAPER
Community Influences on Married Women’s Safer Sex Negotiation Attitudes in Bangladesh: A Multilevel Analysis Syeda S. Jesmin1 • Cynthia M. Cready2
Received: 22 August 2014 / Revised: 17 January 2015 / Accepted: 29 March 2015 Springer Science+Business Media New York 2015
Abstract The influence of disadvantaged or deprived community on individuals’ health risk-behaviors is increasingly being documented in a growing body of literature. However, little is known about the effects of community characteristics on women’s sexual attitudes and behaviors. To examine community effects on married women’s safer sex negotiation attitudes, we analyzed cross-sectional data from the 2011 Bangladesh Demographic and Health Surveys on a sample of 15,134 married womenin600communities.Weestimatedtwomultilevellogistic regressionmodels.Model1,whichincludedonlyindividual-level variables, showed that women’s autonomy/empowerment, age, and HIV knowledge had significant associations with their safer sex negotiation attitudes. We did not find any socioeconomic status gradient in safer sex negotiation attitudes at the individual level. Adding community-level variables in Model 2 significantly improved the fit of the model. Strikingly, we found that higher community-level poverty was associated with greater positive safer sex negotiation attitudes. Prevailing gender norms and overall women’s empowerment in the community also had significant effects. While research on community influences calls for focusing on disadvantagedcommunities,ourresearchhighlightstheimportanceof not underestimating the challenges that married women in economically privileged communities may face in negotiating safer sex. To have sufficient and equitable impact on married women’s sexual and reproductive health, sexual and reproductive health
& Syeda S. Jesmin [email protected] 1
Department of Sociology and Psychology, University of North Texas at Dallas, 7400 University Hills Blvd., Dallas, TX 75241, USA
2
Department of Sociology, University of North Texas, Denton, TX 76203-5017, USA
promotion policies and programs need to be directed to women in wealthier communities as well. Keywords Bangladesh Community Women Safer sex negotiation Sexually transmitted infections
Introduction Globallyeverydaynearly1million peopleacquireanew sexually transmitted infection (STI), 80–90 % of which occur in the developing world (World Health Organization [WHO], 2013). Women, particularly, are at greater risk of STI contraction as socialandpoliticalfactorsinteractwiththeirbiologicalvulnerability (Ostrach & Singer, 2012). Being married has been reported to exacerbate women’s risk of STI contraction (Hirsch, 2007; Tenkorang, 2012). To reduce married women’s risk for STIs, it is important to understand the factors that are associated with their safer sex practices. The impact of personal characteristics, including socioeconomic status (SES), gender norms, and relationship power, on married women’s sex negotiation is well documented (Golobof, Weine, Bahromov, & Luo, 2011; Jesmin & Cready, 2014; Kordoutis, Loumakou, & Sarafidou, 2000; Lotfi, Tehrani, Khoei, Yaghmaei, & Dworkin,2013; Popoola, 2009; Pulerwitz, Amaro, De Jong, Gortmaker, & Rudd, 2002; Smit, 2008). However, little is known about the association between community characteristics, including community SES and gender norms, and married women’s safer sex practices and attitudes. Most previous studies linking community SES and sexual risk behaviors have focused relatively narrowly on adolescents or young men (Bauermeister, Zimmerman, & Caldwell, 2010; Baumer & South, 2001; Browning, Burrington, Leventhal, & BrooksGunn, 2008; Burgard & Lee-Rife, 2009; Lindberg & Orr, 2011), HIV high-risk populations such as men who have sex with men
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(Frye et al., 2010), and married men (Stephenson, 2010). While these studies suggest an inverse association of community SES and sexual-risk behaviors, a majority of the studies were conducted in the U.S. Thus, it is not clear if community SES has the same effect in developing countries or on married women’s sexual behavior (Burgard & Lee-Rife, 2009; Villarreal & Silva, 2006). The influence of disadvantaged or deprived community on individuals’ health risk behaviors is often explained by: (1) fewer healthy choices due to lack of material goods and services (Lee & Cubbin, 2002; Prentice, 2006); (2) social disorganization (Kerrigan, Witt, Glass, Chung, & Ellen, 2006; Lee & Cubbin, 2002) and its associated stressors and greater exposure to health damaging environment or behavior(Takeuchi, Aida,Morita, Ando,& Osaka, 2012); and (3) strained or limited social networks and their effects on diffusion of health information (Latkin, Kuramoto, Davey-Rothwell, & Tobin, 2010). Individual HIV risk behaviors (i.e., condom use, STIs, multiplepartnerships,andpaidsex)havebeenreportedtobeinfluenced formenbycommunitylevel povertyandcommunityproximityto a major city (Feldacker, Ennett, & Iiene, 2011). Browning et al. (2008) found that community social cohesion measured by collective efficacy, that is, intergenerational connectedness and informal social control, was associated with fewer sexual partners during adolescence. In a relatively rare non-U.S. study, concentrated community SES disadvantage and social disorganization reflected in lack of trust and weak social ties in the community increased young black South Africans’ risk of earlier sexual debut and unprotected sex (Burgard & Lee-Rife, 2009). Other non-U.S. studies have found that higher SES communities expose individuals to greater health information by its diffusion via social networks and peer influence. For example, Andrzejewski, Reed, and White (2009) conducted a study in Ghana and found that, evenifadultsthemselveswereilliterate,livinginacommunitywith a high level of literacy or a regular market increased their health knowledge. Similarly, a recent study by Jesmin and Chaudhuri (2013) revealed that, regardless of their own SES, Bangladeshi women living in SES disadvantaged communities were less knowledgeable of HIV and its prevention than their peers in advantaged communities. Other research has focused more specifically on the effects of network and community norms. Dynes, Stephenson, Rubardt, and Burtel (2012) found that community norms regarding the ideal number of sons had the stronger influence on women’s condom use than their own perception of the ideal number, and therefore living in pervasive pronatalist communities lowered women’s condom use. Similarly, peer and network norms are a critical context for substance abuse (Latkin et al., 2010) and risky sexual behaviors among female adolescents (Salazar et al., 2011). A study in Tajikistan found that migrants’ wives’ abilities to speak about sexual activities, protect themselves from husbands’ HIV, and get HIV testing were limited by familial, cultural, and social norms that influenced them to perceive hus-
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bands as their protectors (Golobof et al., 2011). Even when living in a society with high HIV prevalence such as South Africa, the strong social norm of‘‘being committed to’’compels women to perceive risk of HIV/STI contraction as minimal and preventive behavior as unnecessary (Smit, 2008). We sought to explore the link among women’s safer sex negotiation attitudes and community-level characteristics in a national sample of women in Bangladesh. In 2012, Bangladesh ranked111outof148countriesontheUNDP’sGenderInequality Index, which reflects very high gender-based inequalities in reproductive health, empowerment, and economic activity (United Nations Development Program [UNDP], 2013). Bangladeshi women are subject to many patriarchal norms and practices that severely restrict their reproductive and sexual rights, choices, and preferences. It is taken for granted that the purpose of marriage is to have children, and childbearing is perceived as crucial for marital stability. Forced sex is relatively common within married life and typically husbands are the final decisions makers about whether a condom should be used or not (Khan, Townsend, & D’Costa, 2002). Men are expected to take the primary responsibility for activities that involve the market place while women for managing children and home. Prior research shows that while individual-level traits were important, most of the variations of women’s mobility and authority in Bangladesh could be attributed to sociocultural differences among villages (Balk, 1997). Consistent with previous research, we expected that women living in a community where wife beating is permissive and women lack empowerment would be less likely to negotiate safer sex with their husbands regardless of their individual and household level demographic and SES risk factors. In addition, we expected that women living in economically disadvantaged communities would also be less likely to negotiate safer sex.
Method Participants Dataweredrawn from the2011Bangladesh DemographicHealth Surveys (BDHS). The BDHS’s sampling and data collection methods are detailed elsewhere (Measure DHS, 2013). Briefly, 17,842 interviews were completed with ever-married women of reproductive age with a response rate of 98 % from a representative probability sample of 17,141 households in 600 primary sampling units (PSUs) or ‘‘communities’’ in Bangladesh. The sample for our study consisted of 15,364 women who were age 15–49 years, currently married, and‘‘usual residents.’’After listwise deletion of cases with missing values, the sample reduced to 15,134 participants in 600 communities. The number of participants in a community ranged from 10 to 38, and averaged 25.
Arch Sex Behav
Measures The dependent variable was married women’s safer sex negotiation attitude. It was measured based on responses to the question:‘‘Husbands and wives do not always agree on everything. If a wife knows her husband has a disease that she can get during sexual intercourse, is she justified in refusing to have sex with him?’’(Measure DHS, 2013, p. 360).‘‘Yes’’responses were coded ‘‘1’’and‘‘no’’responses‘‘0.’’The question did not use any terminology that might be unfamiliar to the low-literate or illiterate women; therefore, they needed no prior knowledge of STIs to answer it. About 92 % of women in the sample responded‘‘yes,’’ leaving 8 % who felt that a wife does not have the right to refuse sex if her husband has a disease that she can get during sexual intercourse. Table 1 showstheoperational definitionsand summarystatistics for the explanatory variables. The selection of the individuallevel variables was largely guided by prior research: women’s autonomy/empowerment (Jesmin & Cready, 2014); age (Khan et al., 2002); religion (Sahu & Hutter, 2012); education (Painter, Wingood, DiClemente, DePadilla, & Simpson-Robinson, 2012); employment status; household wealth (Tenkorang, 2012); membership in non-governmental organizations (NGOs) (Jesmin & Chaudhuri, 2013); and knowledge/awareness of HIV/AIDS and other STIs and condom use (Tenkorang, 2012). We used three measures ofwomen’s autonomy/empowerment: (1) freedom of movement outside the home; (2) decision making power in the household; and (3) attitude toward wife beating. Although the Demographic Health Surveys (DHS) of other countries ask about women’s freedom to go to avariety ofplaces outside the home, the 2011 BDHS only asked: (1)‘‘do’’and (2)‘‘can you go to a health center or hospital alone or with your young children?’’ (Measure DHS, 2013, pp. 357–358). Thus, we coded the‘‘freedom of movement’’ variable ‘‘1’’ for women who answered ‘‘yes’’ to either question, indicating mobility, and coded it ‘‘0’’ for women who answered‘‘no’’to both questions, indicating restricted mobility. As the first panel of Table 1 shows, about 43 % of women in the sample had restricted mobility. Women were also asked about their participation in decisions about health care, large household purchases, and visits to family or relatives. Responses for each item were coded‘‘1’’if the woman indicated that she usually made the decision alone or with her husband/partner and ‘‘0’’ if she indicated that she was not involved in making the decision. We summed the recoded responses across the three items to create a ‘‘decision making power in the household’’ index (Cronbach’s a = 0.80). Scores ranged from 0, indicating no involvement in any of the three decisions, to 3, indicating involvement in all three decisions. Women in the sample reported participating in an average of two decisions (M = 1.9, SD = 1.2); 48 % said they participated in all three decisions. We also created an index for attitude toward wife beating. Women’s‘‘yes’’responses to items asking whether a husband is
justified in ‘‘hitting or beating’’ his wife for going out without telling him, neglecting the children, arguing with him, refusing to have sex with him, and burning the food were counted. Thus, the index ranged from 0 to 5 (Cronbach’s a = 0.78). The mean count was on the low end (M = 0.7, SD = 1.2). However, about onethird (32 %) of women in the sample felt that wife beating was justified for at least one of the reasons. Age was an interval-level variable with a range of 15–49 years. Religion was coded ‘‘1’’ for Muslims and ‘‘0’’ for participants of other religions (mostly Hindus). Women in the sample were relatively young (M = 30.9, SD = 9.0) and most (89 %) were Muslim. We used three indicators of women’s SES. Highest level of education completed was measured by three binary variables coded ‘‘1’’ for ‘‘primary,’’‘‘secondary,’’ and ‘‘higher’’ education levels, respectively, with‘‘none’’serving as the reference category. Employment status was measured by two binary variables coded‘‘1’’for full-time and part-time employment, respectively, withnoemployment servingasthereferencecategory.Forhousehold wealth, we used an index constructed by DHS. This index classified households as‘‘poorest’’(in the lowest quintile nationally), ‘‘poorer’’ (second quintile), ‘‘middle’’ (third quintile), ‘‘richer’’(fourth quintile), or‘‘richest’’(top quintile) based on asset ownership and dwelling amenities (Rutstein & Johnson, 2004). We recoded the index into four binary variables, coded ‘‘1’’ for ‘‘poorer,’’ ‘‘middle,’’‘‘richer,’’ and ‘‘richest,’’ respectively, with ‘‘poorest’’serving as the reference category. According to all three measures of SES, women in the sample were relatively disadvantaged. Only 8 % had earned a higher education degree and 26 % had less than a primary school education. In addition, most (86 %) reported no work during the previous year aside from their own housework and 36 % were part of a‘‘poor’’household (i.e., falling into either of the bottom two wealth index quintiles nationally). NGO membership was coded‘‘1’’for membership in a major NGO (i.e., Grameen Bank, Bangladesh Rural Advancement Committee, Bangladesh Rural Development Board, PROSHIKA [stands for three Bengali words for training, education, and action], or ASHA [‘‘hope’’in Bengali]) and‘‘0’’otherwise. About 28 %ofwomeninthesampleindicatedbelongingtoamajorNGO. Knowledge about AIDS and the prevention and transmission oftheAIDSvirusandotherSTIswasmeasuredbythreevariables. The first variable,‘‘HIV/AIDS knowledge index,’’was a count of women’s correct responses to five questions on HIV prevention and transmission (Cronbach’s a = 0.78) (Measure DHS, 2013, pp. 201, 359). Two questions asked about preventive behaviors: (1)‘‘Can people reduce their chance of getting the AIDS virus by using a condom every time they have sex?’’and (2)‘‘Can people reduce their chance of getting the AIDS virus by having just one uninfected sex partner who has no other sex partners?’’The other three questions focused on common misconceptions in Bangladesh about the transmission of the AIDS virus (i.e., believing that one can get the virus from mosquito bites or from sharing food with an infected person or that a‘‘healthy-looking person’’cannot
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Arch Sex Behav Table 1 Descriptive and bivariate statistics for variables in the analysis Variable
Total mean (SD) or %
Range
% Okay for wife to refuse sex if husband has an STI
Individual-level variablesa Can go to health center alone/with children No
42.6
Yes
57.4
Decision-making power index (a = .80)b
1.90 (1.22)
90.6*** 93.4 0–3
Alone or with husband, decides … 0 of 3 items 1 of 3 items
21.9 14.3
88.7*** 89.6
2 of 3 items
15.8
91.9
All 3 items
48.0
Wife-beating attitude index (a = .78)c
0.71 (1.25)
94.7 0–5
Okay for husband to beat wife in … 0 of 5 situations
67.8
1 of 5 situations
12.5
90.6
2 of 5 situations
8.7
91.0
3 of 5 situations
5.8
88.9
4 of 5 situations
2.8
84.9
All 5 situations Age
93.4***
2.4 30.93 (8.99)
87.2 15-49
15–24 years old
28.8
92.3
25–49 years old
71.2
92.2
11.4
92.5
88.6
92.2
None
25.6
92.1*
Primary
30.5
91.6
Secondary
35.8
92.4
8.2
94.1
86.2
92.1
Religion Non-Muslim Muslim Education
Higher Employment status Not employed last year Employed part-time
3.5
91.3
Employed full-time
10.3
93.4
Poorest
17.3
92.0***
Poorer
18.7
91.6
Middle
19.2
92.2
Richer Richest
21.0 23.8
91.0 94.0
Household wealth
NGO membership Not a member
71.9
92.1
Member of at least one
28.1
92.4
HIV/AIDS knowledge index (a = .78)d
2.21 (1.80)
0–5
0 of 5 items correct
31.5
1 of 5 items correct
6.2
90.8
2 of 5 items correct
13.4
91.2
3 of 5 items correct
19.8
92.1
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90.9***
Arch Sex Behav Table 1 continued Variable
Total mean (SD) or %
Range
% Okay for wife to refuse sex if husband has an STI
4 of 5 items correct
17.5
93.7
All 5 items correct
11.7
95.6
Heard of other STIs No
84.8
92.3
Yes
15.2
91.8
Currently use condom No
93.9
92.1
Yes
6.1
93.4
Community-level variablese Proportion of women who can go to the hospital/health center alone/with children
.58 (.16)
B.59
50.6
[.59
49.4
Mean score for women on the decision-making power indexb B1.9
50.2 49.8
Mean score for women on the wife-beating attitude indexc
93.8
B.58
50.4 49.6
Proportion of women who are illiterate
0.7–2.91 89.8*** 94.7
0.70 (0.50)
[.58 B.34 [.34
90.7***
1.88 (0.45)
[1.9
0–1
0–2.64 94.9*** 89.5
.35 (.17)
0–.96
50.3 49.7
Proportion of women who live in a poor household
92.2 92.3
.36 (.27)
0–1
B.33
49.0
92.4
[.33
51.0
92.1
Non-urban
65.1
91.7**
Urban
35.0
93.1
Other
82.7
91.2***
Dhaka
17.3
96.9
Urbanization
Division
STI sexually transmitted infection a
N = 15,134 currently married women in Bangladesh
b
Count of three areas (i.e., own health care, major household purchases, visits to family/relatives) in which the respondent made decisions alone or with her husband
c
Count of five situations (i.e., goes out without telling him, neglects the children, argues with him, refuses sex, burns the food) in which the respondent reported it was okay for a husband to beat his wife
d
Count of correct responses to five questions on HIV prevention and transmission (i.e., risk reduced by using condom always? risk reduced by limiting sex to uninfected, faithful partner? transmitted by mosquito bites? transmitted by sharing food with infected person? healthy-looking person can have the AIDS virus?)
e
N = 600 communities (PSUs) inBangladesh. First five community-level variableswere derived by aggregating the‘‘valid’’responses of all women surveyed to the community level. Total number surveyed in a community ranged from 13 to 42, with an average of 29.7 * p B .05; ** p B .01; *** p B .001 (two-tailed chi square tests)
have it). Women who indicated that they had never‘‘heard of an illness called AIDS’’ were coded ‘‘0’’ on the index. The second variable was a dummy indicating knowledge/awareness of other STIs, with ‘‘yes’’ responses to the question, ‘‘…have you heard about infections that can be transmitted through sexual contact?’’
coded‘‘1’’and‘‘no’’responses‘‘0’’(Measure DHS, 2013, p. 359). The third variable, also a dummy, indicated whether or not the participant currently used a condom during sexual relations (1 = yes; 0 = no). Overall, women in the sample showed a considerable lack of knowledge regarding AIDS and the transmission of
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HIV and other STIs. The average woman only got two correct responses on the HIV/AIDS knowledge index (M = 2.2, SD = 1.8). Only 15 % of the women said they had heard of other STIs. And, only 6 % currently used a condom. The second panel of Table 1 shows the operational definitions and summary statistics for the seven community-level explanatory variables. Five were derived from the BDHS by aggregating the ‘‘valid’’ responses of all women surveyed (ever-married women aged 15-49) to the PSU or ‘‘community’’ level, and representedwomen’sautonomyandSESatthecommunity-level. Fortheanalysis,welinkedthesecommunity-levelvariablestoour study sample using a community identifier. The other two community-level variables were level of urbanization (Veinot & Harris, 2011) and division (Kamal, 2000). As the second panel of Table 1 shows, although women in the average community had relatively limited autonomy or empowerment, levels varied across communities. For example, the percentage of women in the community who were free to go to the hospital/health center without another adult ranged in the sample of communities from near zero to 100. Similarly, the average number of major household decisions in which women in the community participated ranged in communities from near 1 to almost 3, and the average number of situations in which women in the community felt wife beating was justified ranged from 0 to almost 3. Women’s SES at the community-level also varied. Both the proportion illiterate and the proportion in a poor household ranged widely from 0 to near 1 or 1, and averaged .35 and .37, respectively. Most of the communities were located in the ‘‘countryside’’ (Measure DHS, 2013) (65 %) and outside Dhaka division (83 %), where the capital city is located. The last column in Table 1 shows the bivariate relationships between safer sex negotiation attitude and each of the explanatory variables. The belief that a woman has the right to refuse sex if her husband has an STI was progressively more likely among participants with greater mobility and decision making power (p\ .001), less acceptance of wife beating norms (p\.001), higher education (p\.05), more household wealth (p\.001), and better HIV knowledge (p\.001). The belief was also significantly more likely among participants living in communities where women had greater empowerment (p\.001), and among those living in communities located in Dhaka division (p\.001) or other urban areas (p\.01). Procedure All analyses were conducted using Stata 11 (StataCorp, Inc., College Station, TX). Multilevel logistic regression analysis with a random intercept (Stata’s ‘‘xtlogit’’) was used to account for the clustering of participants within PSU or ‘‘community’’ and facilitate the estimation of community-level effects (Rabe-Hesketh & Skrondal, 2012). A‘‘baseline’’or intercept-only model was examined to assess the extent of the dependent variable’s variation between communitiesand theappropriateness ofusingmultilevel
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analysis. According to the results (not shown), the intraclass correlation coefficient (q) was .31. Thus, about 31 % of the variation in married women’s safer sex negotiation attitude was associated with differences between communities. Additionally, based on a likelihood ratio test, the null hypothesis that this variation is zero (and multilevel analysis not required) was rejected (p\.001; see Rabe-Hesketh & Skrondal, 2012, p. 142). Two substantive models were estimated. Model 1 examined the effects of the individual-level variables. Model 2 added the community-level variables. Two-tailed p values are reported to reflect the statistical significance of effects. Model goodness-of-fit was assessed using the deviance or likelihood ratio test and Akaike’s information criterion (AIC). The difference in deviance (-2 log likelihood)oftwonestedmodelshasav2 distributionwithdegrees of freedom equal to the additional number of predictors in the larger model. AIC is an alternative measure of fit that corrects for the number of predictors. Diagnostics indicated no problem with multicollinearity [i.e., tolerance values ranged from 0.39 to 0.98, all well above conventionally accepted cutoffs (e.g., Chatterjee, Hadi, & Price, 2000, p. 240)].
Results Table 2 shows the multilevel logistic regression results. Model 1 examined the effects of the individual-level variables on married women’s safer sex negotiation attitude. Women’s autonomy/ empowerment, age, and HIV/AIDS knowledge had significant effects. Empowerment had positive effects. For example, compared to women with restricted mobility, women who were free togotoahealthcarefacilitywithoutanotheradultwere24 %(1009 [odds ratio - 1] = 100 9 [1.24 - 1] = 24 %) more likely to believe a woman has the right to refuse sex if her husband has an STI (p\.01). Furthermore, women’s odds of holding this belief increased 27 % with each additional area of household decision making in which they were involved, and decreased 11 % with each additional situation in which they felt wife beating was justified (p\.001). Holding empowerment and other individual-level factors constant, age had a negative effect on safer sex negotiation attitude. With each additional year of age, the odds of believing a woman has the right to refuse sex if her husband has an STI decreased 1 % (p\.01). On the other hand, HIV/AIDS knowledge had a significant positive effect on safer sex negotiation attitude (p\.001). That is, with each additional correct response on the knowledge index, the odds of believing a woman has the right to refuse sex if her husband has an STI increased 9 %. None of the other individual-level variables had a statistically significant effect (p[.05). Model 2 added the community-level variables. Their addition significantly improvedthe fit ofthe model (v2 = 93.23, df = 7, p\ .001, AIC = 7474.73) but did not change the effects of the individual-level variables. Personal autonomy/empowerment (p\ .01) and HIV/AIDS knowledge (p\.001) were still associated
Arch Sex Behav Table 2 Multilevel logistic regression models predicting married Bangladeshi women’s safer sex negotiation attitude Variables
Okay for wife to refuse sex if husband has an STI Model 1 B (SE)
Model 2 Odds ratioa
B (SE)
Odds ratioa
Fixed effects Individual-level variablesb Can go to health center alone/with children No (reference) Yes
0.21 (0.07)**
1.24
0.19 (0.07)**
1.21
0.24 (0.03)***
1.27
0.21 (0.03)***
1.24
Wife-beating attitude index
-0.12 (0.02)***
0.89
-0.08 (0.02)***
0.92
Age (in years)
-0.01 (0.00)**
0.99
-0.01 (0.00)**
0.99
0.09 (0.13)
1.10
0.09 (0.12)
1.09
Decision-making power in household index
Religion Non-Muslim (reference) Muslim Education None (reference) Primary
-0.17 (0.09)
0.84
-0.16 (0.09)
0.85
Secondary
-0.23 (0.11)*
0.79
-0.20 (0.11)
0.82
Higher
-0.23 (0.18)
0.80
-0.22 (0.18)
0.80
Employment status Not employed last year (reference) Employed part-time
-0.09 (0.18)
0.91
-0.07 (0.18)
0.93
Employed full-time
-0.01 (0.12)
0.99
-0.04 (0.12)
0.96
-0.03 (0.11)
0.97
-0.01 (0.11)
0.99 1.16
Household wealth Poorest (reference) Poorer Middle
0.10 (0.12)
1.11
0.15 (0.12)
Richer
-0.11 (0.12)
0.90
-0.05 (0.12)
0.95
0.18 (0.14)
1.20
0.19 (0.15)
1.21
Richest NGO membership Not a member (reference) Member of at least one
0.03 (0.08)
1.03
0.03 (0.08)
1.03
0.08 (0.02)***
1.09
0.08 (0.02)***
1.08
-0.10 (0.09)
0.91
-0.07 (0.09)
0.93
-0.06 (0.15)
0.94
-0.07 (0.15)
0.93
Proportion of women who can go to health center alone/with children
0.57 (0.41)
1.77
Mean score of women on decision-making power in household index
0.55 (0.14)***
1.73
Mean score of women on wife-beating attitude index
-0.62 (0.12)***
0.54
Proportion of women who live in a poor household
0.92 (0.34)**
2.52
Proportion of women who are illiterate
0.02 (0.45)
1.02
-0.10 (0.15)
0.90
HIV/AIDS knowledge index Heard of other STIs No (reference) Yes Currently use condom No (reference) Yes Community-level variablesb
Urbanization Non-urban (reference) Urban
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Arch Sex Behav Table 2 continued Variables
Okay for wife to refuse sex if husband has an STI Model 1
Model 2 Odds ratioa
B (SE)
Odds ratioa
B (SE)
Division Other (reference) Dhaka
0.96 (0.18)***
Constant Random effects (intercept only) Between-community variance (Hw) (SE) Intraclass correlation coefficient (q) Log likelihood
2.79 (0.22)***
1.38 (0.43)***
0.28 (0.11)
0.02 (0.12)
.29
.24
-3756.98
-3710.37
7553.96
7474.73
Akaike information criterion (AIC)
2.61
N = 15,134 married women age 15–49 in 600 communities (PSUs) STIs sexually transmitted infections, B (SE) unstandardized logistic regression coefficient estimate (B) and its SE a
Odds ratio = eB
b
See Table 1 for details
* p B .05; ** p B .01; *** p B .001 (two-tailed tests)
with a positive safer sex negotiation attitude, and age was still associated with a negative attitude (p\.01). Among the community-level variables, two of the three measures of prevailing gender norms in the community had significant effects (p\.001). When a woman lived in a community where women were relatively empowered in their households, she was more likely to believe that a woman has the right to refuse sex if her husband has an STI, regardless of how empowered she was in her own household. She was also more likely to endorse this right if she lived in a community where wife beating was less accepted. Community SES also mattered. Specifically, all else equal, women living in a community where the proportion of women in poor households was high were more likely to believe that a woman has the right to refuse sex if her husband has an STI (p\.01). Finally, this belief was more likely among women living in Dhaka division compared to other divisions (p\ .001).
Discussion Using a nationally representative sample of a developing country, our results provide some of the first evidence of the influences of community-level poverty and women empowerment on married women’s safer sex negotiation attitudes. Strikingly, we found that higher community-level poverty was associated with greater positive safer sex negotiation attitudes for married women. This implies that there maybegreater needforsexual health promotion and prevention programs for married women in wealthier communities.
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Our findings revealed that the community-health link suggestedby previousliterature may operate in amore complex manner where women’s sexual health is concerned. Higher poverty in the community may contribute to weaken the norms of male dominance since husbands may struggle to perform their‘‘breadwinner’’ roles adequately (Banks, 2013). Similar to many other developing countries, families in Bangladesh are organized around rigid gender segregated roles where men are ‘‘powerful patriarchs who have full authority over the family including both wives and children,’’and ideal husbands or fathers are those‘‘who successfully play the instrumental roles of being the breadwinners and protectors of the family’’ (Jesmin & Seward, 2011, p. 8). However, in poor communities where marriage does not protect women much from financial insecurity they may feel they can refuse sex if their husbands have STIs with little concern for the consequences (Trail & Karney, 2012). When we controlled for individual-level characteristics, we found that living in communities where wife beating was permissible lowered women’s odds of justifying safer sex negotiation even when they knew that their husbands had STIs. This result was consistent with recent research on intimate partner violence (IPV) that found that women living in areas where wife beating is permissible were more likely to report experiencing physical or sexual violence perpetuated by their husbands (Linos, Slopen, Subramanian, Berkman, & Kawachi, 2013). If IPV is a norm in the community, women may not negotiate safer sex with husbands for fear of a violent reaction (El-Bassel, Gilbert, & Rajah, 2000). Exposure to IPV has been found to decrease women’s confidence in their ability to negotiate safer sex practices, such as condom use, with a partner (Swan & O’Connell, 2012). A considerable number of women in Bangladesh favor inequitable gender
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norms (Sayem & Nury, 2013), some of which are often claimed to bereligiouslysanctionedbutdisadvantagethemfurther.Navedand Persson (2008) noted that Muslim women in Bangladesh traditionally tend to have less mobility and be less vocal about their rights compared to their non-Muslim counterparts. The cultural constructs of gender roles are deeply rooted in the structure of society, such as family, inheritance, and division of labor within the households. Similar to Bangladesh, in many other low-income countries, such as in Iran, women are expected to be sexually ignorant and are socialized to prioritize their husbands’ pleasure and negate their own sexual protection (Lotfi et al., 2013). Rigid genderrolesaresodeeplyrootedintheAfro-SurinameseandDutch Antillean communities in the Netherlands that wives in these communities are less likely to negotiate safer sex in fear of becominglessdesirabletotheirhusbands(Bertens,Krumeich,Borne, & Schaalma, 2008). We also found that women’s odds of positive safer sex negotiation attitudes were higher in neighborhoods where women tend tobeinvolvedinmajorhouseholddecisionsandinneighborhoods located in Dhaka division. Both of these characteristics represent environments with potentially greater opportunities for women. For example, women living in Dhaka division likely face fewer constraints to conform to gender norms due to their proximity to thecountry’scapitalcityanditsrelativelyprogressiveatmosphere (Jesmin & Cready, 2014). These women also likely benefit from the division’s formal sectoremployment options, especially in the garmentssector(United NationsConference onTrade and Development, 2012). For cash-income dependent households in the division, women’s employment in the formal sector represent both a‘‘necessary evil’’for survival and a‘‘strategy for advancement’’ (Banks, 2013, p. 99). Examining the effects of women’s employment on low-income household dynamics in Dhaka, Banks (2013) noted that while wives’ employment can lead to marital tensions and husbands’ negative behaviors, when ‘‘husbands do not behave in line with household interests’’ wives‘‘may vocally challenge their husbands because these behaviors reduce the impact that their additional labor has on the household’’ (p. 106). It seems reasonable that these dynamics could motivate married women to negotiate for safer sex. Several limitations of this study should be noted. First, since we used opinions on sexuality collected from self-reports of women in a conservative society, we cannot reject the possibility of social desirability response bias in the data (Meston, Heiman, Trapnell, & Paulhus, 1998). Second, the 600 ‘‘communities’’ (PSUs) in our study were administrative and small geographic units, which may or may not reflect functional communities or neighborhoods. Moreover, social cohesion and interaction are not necessarily bounded geographically (Diez Roux, 2001). Additionally, our study was cross-sectional. Longitudinal dimensions should be considered in future studies. For example,
living in a community that has been recently impoverished may not have same effect as living in a chronically impoverished community. Despite these limitations, our findings are generalizable to similar settings in developingcountriesbecause ofthe large and representative sample. Given that the burden of STIs is greatest in low-income countries and combating STIs is one of the core aspects of WHO’s Global Strategy on Reproductive Health (WHO, 2013), our findings have important public health policy implications. We recommend the development of STI awareness and prevention programs that target married women. While research on community influences calls for focusing on disadvantaged communities (e.g., Jesmin & Chaudhuri, 2013; Lindberg & Orr, 2011), our research highlights the importance of not underestimating the challenges that married women in economically privileged communities face in negotiating safer sex. Women in wealthier communities may have greater access to diagnosis and treatment; however, lack of safer sex negotiation power may put these women at higherriskofcontractingSTIsinthefirstplace.Ourstudyidentified two patterns that can inform sexual health promotion programs. First, community context matters. For example, program messages and strategies that acknowledge the influence of prevailing gender norms and women’s empowerment in the community are warranted. Mass media use, including the use of radio and television campaigns, has been shown to influence safer sex attitudes, norms, and practices (Farr, Witte, Jarato, & Menard, 2005) and, thus, is a promising strategy for changing gender norms and women’s empowerment in communities. Other strategies include empowering women through microfinance-based interventions. For example, Kim et al. (2007) tested such an intervention to reduce IPV in rural South Africa. They implemented Intervention with Microfinance for AIDS and Gender Equity (IMAGE), which combined participatory training in several areas, including domestic violence, HIV and sexuality, and gender roles, with a microfinance program. After 2 years, significant increases in women’s awareness and empowerment and significant decreases in IPV were observed in the intervention villages compared to the control villages. In summary, our results underscore the benefit of communitycontext specific intervention programs for STIs among married women. In the global effort to promote sexual and reproductive rights of women in low- and middle-income countries, WHO and the World Bank and many other international organizations have been collaborating with governments and local partners (WHO, 2012). Generation of knowledge to identify the most vulnerable groups of women is critical to design efficient programs. Sexual and reproductive health promotion programs targeted only to the poorest communities may not be sufficient. To have the greatest impact on women’s sexual and reproductive health, policies and programs need to be directed to women in wealthier communities as well.
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Takeuchi, K., Aida, J., Morita, M., Ando, Y., & Osaka, K. (2012). Community-level socioeconomic status and parental smoking in Japan. Social Science and Medicine, 75, 747–751. doi:10.1016/j.socscimed. 2012.04.001. Tenkorang, E. Y. (2012). Negotiating safer sex among married women in Ghana. Archives of Sexual Behavior, 41, 1353–1362. Trail, T. E., & Karney, B. R. (2012). What’s (not) wrong with low-income marriages. Journal of Marriage and Family, 74, 413–427. UNDP. (2013). Human development report, 2013. Retrieved from http://hdr. undp.org/sites/default/files/Country-Profiles/BGD.pdf. United Nations Conference on Trade and Development. (2012). Sectorspecific investment strategy and action plan. Retrieved from http:// unctad.org/Sections/diae_dir/docs/diae_G20_Bangladesh_en.pdf. Veinot, T. C., & Harris, R. (2011). Talking about, knowing about HIV/AIDS inCanada:Arural-urbancomparison.JournalofRuralHealth,27,310– 318. Villarreal, A., & Silva, B. A. (2006). Social cohesion, criminal victimization and perceived risk of crime in Brazilian neighborhoods. Social Forces, 84, 1725–1753. World Health Organization. (2012). H4?: Review of progress, results, and plans. Retrieved from http://www.who.int/reproductivehealth/global_ strategy_women_children/H4briefSept2012.pdf?ua=1. World Health Organization. (2013). Sexually transmitted infections (STIs): Key points for action. Retrieved from http://apps.who.int/iris/bitstream/ 10665/82207/1/WHO_RHR_13.02_eng.pdf.
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ORIGINAL PAPER
Community Influences on Married Women’s Safer Sex Negotiation Attitudes in Bangladesh: A Multilevel Analysis Syeda S. Jesmin1 • Cynthia M. Cready2
Received: 22 August 2014 / Revised: 17 January 2015 / Accepted: 29 March 2015 Springer Science+Business Media New York 2015
Abstract The influence of disadvantaged or deprived community on individuals’ health risk-behaviors is increasingly being documented in a growing body of literature. However, little is known about the effects of community characteristics on women’s sexual attitudes and behaviors. To examine community effects on married women’s safer sex negotiation attitudes, we analyzed cross-sectional data from the 2011 Bangladesh Demographic and Health Surveys on a sample of 15,134 married womenin600communities.Weestimatedtwomultilevellogistic regressionmodels.Model1,whichincludedonlyindividual-level variables, showed that women’s autonomy/empowerment, age, and HIV knowledge had significant associations with their safer sex negotiation attitudes. We did not find any socioeconomic status gradient in safer sex negotiation attitudes at the individual level. Adding community-level variables in Model 2 significantly improved the fit of the model. Strikingly, we found that higher community-level poverty was associated with greater positive safer sex negotiation attitudes. Prevailing gender norms and overall women’s empowerment in the community also had significant effects. While research on community influences calls for focusing on disadvantagedcommunities,ourresearchhighlightstheimportanceof not underestimating the challenges that married women in economically privileged communities may face in negotiating safer sex. To have sufficient and equitable impact on married women’s sexual and reproductive health, sexual and reproductive health
& Syeda S. Jesmin [email protected] 1
Department of Sociology and Psychology, University of North Texas at Dallas, 7400 University Hills Blvd., Dallas, TX 75241, USA
2
Department of Sociology, University of North Texas, Denton, TX 76203-5017, USA
promotion policies and programs need to be directed to women in wealthier communities as well. Keywords Bangladesh Community Women Safer sex negotiation Sexually transmitted infections
Introduction Globallyeverydaynearly1million peopleacquireanew sexually transmitted infection (STI), 80–90 % of which occur in the developing world (World Health Organization [WHO], 2013). Women, particularly, are at greater risk of STI contraction as socialandpoliticalfactorsinteractwiththeirbiologicalvulnerability (Ostrach & Singer, 2012). Being married has been reported to exacerbate women’s risk of STI contraction (Hirsch, 2007; Tenkorang, 2012). To reduce married women’s risk for STIs, it is important to understand the factors that are associated with their safer sex practices. The impact of personal characteristics, including socioeconomic status (SES), gender norms, and relationship power, on married women’s sex negotiation is well documented (Golobof, Weine, Bahromov, & Luo, 2011; Jesmin & Cready, 2014; Kordoutis, Loumakou, & Sarafidou, 2000; Lotfi, Tehrani, Khoei, Yaghmaei, & Dworkin,2013; Popoola, 2009; Pulerwitz, Amaro, De Jong, Gortmaker, & Rudd, 2002; Smit, 2008). However, little is known about the association between community characteristics, including community SES and gender norms, and married women’s safer sex practices and attitudes. Most previous studies linking community SES and sexual risk behaviors have focused relatively narrowly on adolescents or young men (Bauermeister, Zimmerman, & Caldwell, 2010; Baumer & South, 2001; Browning, Burrington, Leventhal, & BrooksGunn, 2008; Burgard & Lee-Rife, 2009; Lindberg & Orr, 2011), HIV high-risk populations such as men who have sex with men
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(Frye et al., 2010), and married men (Stephenson, 2010). While these studies suggest an inverse association of community SES and sexual-risk behaviors, a majority of the studies were conducted in the U.S. Thus, it is not clear if community SES has the same effect in developing countries or on married women’s sexual behavior (Burgard & Lee-Rife, 2009; Villarreal & Silva, 2006). The influence of disadvantaged or deprived community on individuals’ health risk behaviors is often explained by: (1) fewer healthy choices due to lack of material goods and services (Lee & Cubbin, 2002; Prentice, 2006); (2) social disorganization (Kerrigan, Witt, Glass, Chung, & Ellen, 2006; Lee & Cubbin, 2002) and its associated stressors and greater exposure to health damaging environment or behavior(Takeuchi, Aida,Morita, Ando,& Osaka, 2012); and (3) strained or limited social networks and their effects on diffusion of health information (Latkin, Kuramoto, Davey-Rothwell, & Tobin, 2010). Individual HIV risk behaviors (i.e., condom use, STIs, multiplepartnerships,andpaidsex)havebeenreportedtobeinfluenced formenbycommunitylevel povertyandcommunityproximityto a major city (Feldacker, Ennett, & Iiene, 2011). Browning et al. (2008) found that community social cohesion measured by collective efficacy, that is, intergenerational connectedness and informal social control, was associated with fewer sexual partners during adolescence. In a relatively rare non-U.S. study, concentrated community SES disadvantage and social disorganization reflected in lack of trust and weak social ties in the community increased young black South Africans’ risk of earlier sexual debut and unprotected sex (Burgard & Lee-Rife, 2009). Other non-U.S. studies have found that higher SES communities expose individuals to greater health information by its diffusion via social networks and peer influence. For example, Andrzejewski, Reed, and White (2009) conducted a study in Ghana and found that, evenifadultsthemselveswereilliterate,livinginacommunitywith a high level of literacy or a regular market increased their health knowledge. Similarly, a recent study by Jesmin and Chaudhuri (2013) revealed that, regardless of their own SES, Bangladeshi women living in SES disadvantaged communities were less knowledgeable of HIV and its prevention than their peers in advantaged communities. Other research has focused more specifically on the effects of network and community norms. Dynes, Stephenson, Rubardt, and Burtel (2012) found that community norms regarding the ideal number of sons had the stronger influence on women’s condom use than their own perception of the ideal number, and therefore living in pervasive pronatalist communities lowered women’s condom use. Similarly, peer and network norms are a critical context for substance abuse (Latkin et al., 2010) and risky sexual behaviors among female adolescents (Salazar et al., 2011). A study in Tajikistan found that migrants’ wives’ abilities to speak about sexual activities, protect themselves from husbands’ HIV, and get HIV testing were limited by familial, cultural, and social norms that influenced them to perceive hus-
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bands as their protectors (Golobof et al., 2011). Even when living in a society with high HIV prevalence such as South Africa, the strong social norm of‘‘being committed to’’compels women to perceive risk of HIV/STI contraction as minimal and preventive behavior as unnecessary (Smit, 2008). We sought to explore the link among women’s safer sex negotiation attitudes and community-level characteristics in a national sample of women in Bangladesh. In 2012, Bangladesh ranked111outof148countriesontheUNDP’sGenderInequality Index, which reflects very high gender-based inequalities in reproductive health, empowerment, and economic activity (United Nations Development Program [UNDP], 2013). Bangladeshi women are subject to many patriarchal norms and practices that severely restrict their reproductive and sexual rights, choices, and preferences. It is taken for granted that the purpose of marriage is to have children, and childbearing is perceived as crucial for marital stability. Forced sex is relatively common within married life and typically husbands are the final decisions makers about whether a condom should be used or not (Khan, Townsend, & D’Costa, 2002). Men are expected to take the primary responsibility for activities that involve the market place while women for managing children and home. Prior research shows that while individual-level traits were important, most of the variations of women’s mobility and authority in Bangladesh could be attributed to sociocultural differences among villages (Balk, 1997). Consistent with previous research, we expected that women living in a community where wife beating is permissive and women lack empowerment would be less likely to negotiate safer sex with their husbands regardless of their individual and household level demographic and SES risk factors. In addition, we expected that women living in economically disadvantaged communities would also be less likely to negotiate safer sex.
Method Participants Dataweredrawn from the2011Bangladesh DemographicHealth Surveys (BDHS). The BDHS’s sampling and data collection methods are detailed elsewhere (Measure DHS, 2013). Briefly, 17,842 interviews were completed with ever-married women of reproductive age with a response rate of 98 % from a representative probability sample of 17,141 households in 600 primary sampling units (PSUs) or ‘‘communities’’ in Bangladesh. The sample for our study consisted of 15,364 women who were age 15–49 years, currently married, and‘‘usual residents.’’After listwise deletion of cases with missing values, the sample reduced to 15,134 participants in 600 communities. The number of participants in a community ranged from 10 to 38, and averaged 25.
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Measures The dependent variable was married women’s safer sex negotiation attitude. It was measured based on responses to the question:‘‘Husbands and wives do not always agree on everything. If a wife knows her husband has a disease that she can get during sexual intercourse, is she justified in refusing to have sex with him?’’(Measure DHS, 2013, p. 360).‘‘Yes’’responses were coded ‘‘1’’and‘‘no’’responses‘‘0.’’The question did not use any terminology that might be unfamiliar to the low-literate or illiterate women; therefore, they needed no prior knowledge of STIs to answer it. About 92 % of women in the sample responded‘‘yes,’’ leaving 8 % who felt that a wife does not have the right to refuse sex if her husband has a disease that she can get during sexual intercourse. Table 1 showstheoperational definitionsand summarystatistics for the explanatory variables. The selection of the individuallevel variables was largely guided by prior research: women’s autonomy/empowerment (Jesmin & Cready, 2014); age (Khan et al., 2002); religion (Sahu & Hutter, 2012); education (Painter, Wingood, DiClemente, DePadilla, & Simpson-Robinson, 2012); employment status; household wealth (Tenkorang, 2012); membership in non-governmental organizations (NGOs) (Jesmin & Chaudhuri, 2013); and knowledge/awareness of HIV/AIDS and other STIs and condom use (Tenkorang, 2012). We used three measures ofwomen’s autonomy/empowerment: (1) freedom of movement outside the home; (2) decision making power in the household; and (3) attitude toward wife beating. Although the Demographic Health Surveys (DHS) of other countries ask about women’s freedom to go to avariety ofplaces outside the home, the 2011 BDHS only asked: (1)‘‘do’’and (2)‘‘can you go to a health center or hospital alone or with your young children?’’ (Measure DHS, 2013, pp. 357–358). Thus, we coded the‘‘freedom of movement’’ variable ‘‘1’’ for women who answered ‘‘yes’’ to either question, indicating mobility, and coded it ‘‘0’’ for women who answered‘‘no’’to both questions, indicating restricted mobility. As the first panel of Table 1 shows, about 43 % of women in the sample had restricted mobility. Women were also asked about their participation in decisions about health care, large household purchases, and visits to family or relatives. Responses for each item were coded‘‘1’’if the woman indicated that she usually made the decision alone or with her husband/partner and ‘‘0’’ if she indicated that she was not involved in making the decision. We summed the recoded responses across the three items to create a ‘‘decision making power in the household’’ index (Cronbach’s a = 0.80). Scores ranged from 0, indicating no involvement in any of the three decisions, to 3, indicating involvement in all three decisions. Women in the sample reported participating in an average of two decisions (M = 1.9, SD = 1.2); 48 % said they participated in all three decisions. We also created an index for attitude toward wife beating. Women’s‘‘yes’’responses to items asking whether a husband is
justified in ‘‘hitting or beating’’ his wife for going out without telling him, neglecting the children, arguing with him, refusing to have sex with him, and burning the food were counted. Thus, the index ranged from 0 to 5 (Cronbach’s a = 0.78). The mean count was on the low end (M = 0.7, SD = 1.2). However, about onethird (32 %) of women in the sample felt that wife beating was justified for at least one of the reasons. Age was an interval-level variable with a range of 15–49 years. Religion was coded ‘‘1’’ for Muslims and ‘‘0’’ for participants of other religions (mostly Hindus). Women in the sample were relatively young (M = 30.9, SD = 9.0) and most (89 %) were Muslim. We used three indicators of women’s SES. Highest level of education completed was measured by three binary variables coded ‘‘1’’ for ‘‘primary,’’‘‘secondary,’’ and ‘‘higher’’ education levels, respectively, with‘‘none’’serving as the reference category. Employment status was measured by two binary variables coded‘‘1’’for full-time and part-time employment, respectively, withnoemployment servingasthereferencecategory.Forhousehold wealth, we used an index constructed by DHS. This index classified households as‘‘poorest’’(in the lowest quintile nationally), ‘‘poorer’’ (second quintile), ‘‘middle’’ (third quintile), ‘‘richer’’(fourth quintile), or‘‘richest’’(top quintile) based on asset ownership and dwelling amenities (Rutstein & Johnson, 2004). We recoded the index into four binary variables, coded ‘‘1’’ for ‘‘poorer,’’ ‘‘middle,’’‘‘richer,’’ and ‘‘richest,’’ respectively, with ‘‘poorest’’serving as the reference category. According to all three measures of SES, women in the sample were relatively disadvantaged. Only 8 % had earned a higher education degree and 26 % had less than a primary school education. In addition, most (86 %) reported no work during the previous year aside from their own housework and 36 % were part of a‘‘poor’’household (i.e., falling into either of the bottom two wealth index quintiles nationally). NGO membership was coded‘‘1’’for membership in a major NGO (i.e., Grameen Bank, Bangladesh Rural Advancement Committee, Bangladesh Rural Development Board, PROSHIKA [stands for three Bengali words for training, education, and action], or ASHA [‘‘hope’’in Bengali]) and‘‘0’’otherwise. About 28 %ofwomeninthesampleindicatedbelongingtoamajorNGO. Knowledge about AIDS and the prevention and transmission oftheAIDSvirusandotherSTIswasmeasuredbythreevariables. The first variable,‘‘HIV/AIDS knowledge index,’’was a count of women’s correct responses to five questions on HIV prevention and transmission (Cronbach’s a = 0.78) (Measure DHS, 2013, pp. 201, 359). Two questions asked about preventive behaviors: (1)‘‘Can people reduce their chance of getting the AIDS virus by using a condom every time they have sex?’’and (2)‘‘Can people reduce their chance of getting the AIDS virus by having just one uninfected sex partner who has no other sex partners?’’The other three questions focused on common misconceptions in Bangladesh about the transmission of the AIDS virus (i.e., believing that one can get the virus from mosquito bites or from sharing food with an infected person or that a‘‘healthy-looking person’’cannot
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Arch Sex Behav Table 1 Descriptive and bivariate statistics for variables in the analysis Variable
Total mean (SD) or %
Range
% Okay for wife to refuse sex if husband has an STI
Individual-level variablesa Can go to health center alone/with children No
42.6
Yes
57.4
Decision-making power index (a = .80)b
1.90 (1.22)
90.6*** 93.4 0–3
Alone or with husband, decides … 0 of 3 items 1 of 3 items
21.9 14.3
88.7*** 89.6
2 of 3 items
15.8
91.9
All 3 items
48.0
Wife-beating attitude index (a = .78)c
0.71 (1.25)
94.7 0–5
Okay for husband to beat wife in … 0 of 5 situations
67.8
1 of 5 situations
12.5
90.6
2 of 5 situations
8.7
91.0
3 of 5 situations
5.8
88.9
4 of 5 situations
2.8
84.9
All 5 situations Age
93.4***
2.4 30.93 (8.99)
87.2 15-49
15–24 years old
28.8
92.3
25–49 years old
71.2
92.2
11.4
92.5
88.6
92.2
None
25.6
92.1*
Primary
30.5
91.6
Secondary
35.8
92.4
8.2
94.1
86.2
92.1
Religion Non-Muslim Muslim Education
Higher Employment status Not employed last year Employed part-time
3.5
91.3
Employed full-time
10.3
93.4
Poorest
17.3
92.0***
Poorer
18.7
91.6
Middle
19.2
92.2
Richer Richest
21.0 23.8
91.0 94.0
Household wealth
NGO membership Not a member
71.9
92.1
Member of at least one
28.1
92.4
HIV/AIDS knowledge index (a = .78)d
2.21 (1.80)
0–5
0 of 5 items correct
31.5
1 of 5 items correct
6.2
90.8
2 of 5 items correct
13.4
91.2
3 of 5 items correct
19.8
92.1
123
90.9***
Arch Sex Behav Table 1 continued Variable
Total mean (SD) or %
Range
% Okay for wife to refuse sex if husband has an STI
4 of 5 items correct
17.5
93.7
All 5 items correct
11.7
95.6
Heard of other STIs No
84.8
92.3
Yes
15.2
91.8
Currently use condom No
93.9
92.1
Yes
6.1
93.4
Community-level variablese Proportion of women who can go to the hospital/health center alone/with children
.58 (.16)
B.59
50.6
[.59
49.4
Mean score for women on the decision-making power indexb B1.9
50.2 49.8
Mean score for women on the wife-beating attitude indexc
93.8
B.58
50.4 49.6
Proportion of women who are illiterate
0.7–2.91 89.8*** 94.7
0.70 (0.50)
[.58 B.34 [.34
90.7***
1.88 (0.45)
[1.9
0–1
0–2.64 94.9*** 89.5
.35 (.17)
0–.96
50.3 49.7
Proportion of women who live in a poor household
92.2 92.3
.36 (.27)
0–1
B.33
49.0
92.4
[.33
51.0
92.1
Non-urban
65.1
91.7**
Urban
35.0
93.1
Other
82.7
91.2***
Dhaka
17.3
96.9
Urbanization
Division
STI sexually transmitted infection a
N = 15,134 currently married women in Bangladesh
b
Count of three areas (i.e., own health care, major household purchases, visits to family/relatives) in which the respondent made decisions alone or with her husband
c
Count of five situations (i.e., goes out without telling him, neglects the children, argues with him, refuses sex, burns the food) in which the respondent reported it was okay for a husband to beat his wife
d
Count of correct responses to five questions on HIV prevention and transmission (i.e., risk reduced by using condom always? risk reduced by limiting sex to uninfected, faithful partner? transmitted by mosquito bites? transmitted by sharing food with infected person? healthy-looking person can have the AIDS virus?)
e
N = 600 communities (PSUs) inBangladesh. First five community-level variableswere derived by aggregating the‘‘valid’’responses of all women surveyed to the community level. Total number surveyed in a community ranged from 13 to 42, with an average of 29.7 * p B .05; ** p B .01; *** p B .001 (two-tailed chi square tests)
have it). Women who indicated that they had never‘‘heard of an illness called AIDS’’ were coded ‘‘0’’ on the index. The second variable was a dummy indicating knowledge/awareness of other STIs, with ‘‘yes’’ responses to the question, ‘‘…have you heard about infections that can be transmitted through sexual contact?’’
coded‘‘1’’and‘‘no’’responses‘‘0’’(Measure DHS, 2013, p. 359). The third variable, also a dummy, indicated whether or not the participant currently used a condom during sexual relations (1 = yes; 0 = no). Overall, women in the sample showed a considerable lack of knowledge regarding AIDS and the transmission of
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HIV and other STIs. The average woman only got two correct responses on the HIV/AIDS knowledge index (M = 2.2, SD = 1.8). Only 15 % of the women said they had heard of other STIs. And, only 6 % currently used a condom. The second panel of Table 1 shows the operational definitions and summary statistics for the seven community-level explanatory variables. Five were derived from the BDHS by aggregating the ‘‘valid’’ responses of all women surveyed (ever-married women aged 15-49) to the PSU or ‘‘community’’ level, and representedwomen’sautonomyandSESatthecommunity-level. Fortheanalysis,welinkedthesecommunity-levelvariablestoour study sample using a community identifier. The other two community-level variables were level of urbanization (Veinot & Harris, 2011) and division (Kamal, 2000). As the second panel of Table 1 shows, although women in the average community had relatively limited autonomy or empowerment, levels varied across communities. For example, the percentage of women in the community who were free to go to the hospital/health center without another adult ranged in the sample of communities from near zero to 100. Similarly, the average number of major household decisions in which women in the community participated ranged in communities from near 1 to almost 3, and the average number of situations in which women in the community felt wife beating was justified ranged from 0 to almost 3. Women’s SES at the community-level also varied. Both the proportion illiterate and the proportion in a poor household ranged widely from 0 to near 1 or 1, and averaged .35 and .37, respectively. Most of the communities were located in the ‘‘countryside’’ (Measure DHS, 2013) (65 %) and outside Dhaka division (83 %), where the capital city is located. The last column in Table 1 shows the bivariate relationships between safer sex negotiation attitude and each of the explanatory variables. The belief that a woman has the right to refuse sex if her husband has an STI was progressively more likely among participants with greater mobility and decision making power (p\ .001), less acceptance of wife beating norms (p\.001), higher education (p\.05), more household wealth (p\.001), and better HIV knowledge (p\.001). The belief was also significantly more likely among participants living in communities where women had greater empowerment (p\.001), and among those living in communities located in Dhaka division (p\.001) or other urban areas (p\.01). Procedure All analyses were conducted using Stata 11 (StataCorp, Inc., College Station, TX). Multilevel logistic regression analysis with a random intercept (Stata’s ‘‘xtlogit’’) was used to account for the clustering of participants within PSU or ‘‘community’’ and facilitate the estimation of community-level effects (Rabe-Hesketh & Skrondal, 2012). A‘‘baseline’’or intercept-only model was examined to assess the extent of the dependent variable’s variation between communitiesand theappropriateness ofusingmultilevel
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analysis. According to the results (not shown), the intraclass correlation coefficient (q) was .31. Thus, about 31 % of the variation in married women’s safer sex negotiation attitude was associated with differences between communities. Additionally, based on a likelihood ratio test, the null hypothesis that this variation is zero (and multilevel analysis not required) was rejected (p\.001; see Rabe-Hesketh & Skrondal, 2012, p. 142). Two substantive models were estimated. Model 1 examined the effects of the individual-level variables. Model 2 added the community-level variables. Two-tailed p values are reported to reflect the statistical significance of effects. Model goodness-of-fit was assessed using the deviance or likelihood ratio test and Akaike’s information criterion (AIC). The difference in deviance (-2 log likelihood)oftwonestedmodelshasav2 distributionwithdegrees of freedom equal to the additional number of predictors in the larger model. AIC is an alternative measure of fit that corrects for the number of predictors. Diagnostics indicated no problem with multicollinearity [i.e., tolerance values ranged from 0.39 to 0.98, all well above conventionally accepted cutoffs (e.g., Chatterjee, Hadi, & Price, 2000, p. 240)].
Results Table 2 shows the multilevel logistic regression results. Model 1 examined the effects of the individual-level variables on married women’s safer sex negotiation attitude. Women’s autonomy/ empowerment, age, and HIV/AIDS knowledge had significant effects. Empowerment had positive effects. For example, compared to women with restricted mobility, women who were free togotoahealthcarefacilitywithoutanotheradultwere24 %(1009 [odds ratio - 1] = 100 9 [1.24 - 1] = 24 %) more likely to believe a woman has the right to refuse sex if her husband has an STI (p\.01). Furthermore, women’s odds of holding this belief increased 27 % with each additional area of household decision making in which they were involved, and decreased 11 % with each additional situation in which they felt wife beating was justified (p\.001). Holding empowerment and other individual-level factors constant, age had a negative effect on safer sex negotiation attitude. With each additional year of age, the odds of believing a woman has the right to refuse sex if her husband has an STI decreased 1 % (p\.01). On the other hand, HIV/AIDS knowledge had a significant positive effect on safer sex negotiation attitude (p\.001). That is, with each additional correct response on the knowledge index, the odds of believing a woman has the right to refuse sex if her husband has an STI increased 9 %. None of the other individual-level variables had a statistically significant effect (p[.05). Model 2 added the community-level variables. Their addition significantly improvedthe fit ofthe model (v2 = 93.23, df = 7, p\ .001, AIC = 7474.73) but did not change the effects of the individual-level variables. Personal autonomy/empowerment (p\ .01) and HIV/AIDS knowledge (p\.001) were still associated
Arch Sex Behav Table 2 Multilevel logistic regression models predicting married Bangladeshi women’s safer sex negotiation attitude Variables
Okay for wife to refuse sex if husband has an STI Model 1 B (SE)
Model 2 Odds ratioa
B (SE)
Odds ratioa
Fixed effects Individual-level variablesb Can go to health center alone/with children No (reference) Yes
0.21 (0.07)**
1.24
0.19 (0.07)**
1.21
0.24 (0.03)***
1.27
0.21 (0.03)***
1.24
Wife-beating attitude index
-0.12 (0.02)***
0.89
-0.08 (0.02)***
0.92
Age (in years)
-0.01 (0.00)**
0.99
-0.01 (0.00)**
0.99
0.09 (0.13)
1.10
0.09 (0.12)
1.09
Decision-making power in household index
Religion Non-Muslim (reference) Muslim Education None (reference) Primary
-0.17 (0.09)
0.84
-0.16 (0.09)
0.85
Secondary
-0.23 (0.11)*
0.79
-0.20 (0.11)
0.82
Higher
-0.23 (0.18)
0.80
-0.22 (0.18)
0.80
Employment status Not employed last year (reference) Employed part-time
-0.09 (0.18)
0.91
-0.07 (0.18)
0.93
Employed full-time
-0.01 (0.12)
0.99
-0.04 (0.12)
0.96
-0.03 (0.11)
0.97
-0.01 (0.11)
0.99 1.16
Household wealth Poorest (reference) Poorer Middle
0.10 (0.12)
1.11
0.15 (0.12)
Richer
-0.11 (0.12)
0.90
-0.05 (0.12)
0.95
0.18 (0.14)
1.20
0.19 (0.15)
1.21
Richest NGO membership Not a member (reference) Member of at least one
0.03 (0.08)
1.03
0.03 (0.08)
1.03
0.08 (0.02)***
1.09
0.08 (0.02)***
1.08
-0.10 (0.09)
0.91
-0.07 (0.09)
0.93
-0.06 (0.15)
0.94
-0.07 (0.15)
0.93
Proportion of women who can go to health center alone/with children
0.57 (0.41)
1.77
Mean score of women on decision-making power in household index
0.55 (0.14)***
1.73
Mean score of women on wife-beating attitude index
-0.62 (0.12)***
0.54
Proportion of women who live in a poor household
0.92 (0.34)**
2.52
Proportion of women who are illiterate
0.02 (0.45)
1.02
-0.10 (0.15)
0.90
HIV/AIDS knowledge index Heard of other STIs No (reference) Yes Currently use condom No (reference) Yes Community-level variablesb
Urbanization Non-urban (reference) Urban
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Arch Sex Behav Table 2 continued Variables
Okay for wife to refuse sex if husband has an STI Model 1
Model 2 Odds ratioa
B (SE)
Odds ratioa
B (SE)
Division Other (reference) Dhaka
0.96 (0.18)***
Constant Random effects (intercept only) Between-community variance (Hw) (SE) Intraclass correlation coefficient (q) Log likelihood
2.79 (0.22)***
1.38 (0.43)***
0.28 (0.11)
0.02 (0.12)
.29
.24
-3756.98
-3710.37
7553.96
7474.73
Akaike information criterion (AIC)
2.61
N = 15,134 married women age 15–49 in 600 communities (PSUs) STIs sexually transmitted infections, B (SE) unstandardized logistic regression coefficient estimate (B) and its SE a
Odds ratio = eB
b
See Table 1 for details
* p B .05; ** p B .01; *** p B .001 (two-tailed tests)
with a positive safer sex negotiation attitude, and age was still associated with a negative attitude (p\.01). Among the community-level variables, two of the three measures of prevailing gender norms in the community had significant effects (p\.001). When a woman lived in a community where women were relatively empowered in their households, she was more likely to believe that a woman has the right to refuse sex if her husband has an STI, regardless of how empowered she was in her own household. She was also more likely to endorse this right if she lived in a community where wife beating was less accepted. Community SES also mattered. Specifically, all else equal, women living in a community where the proportion of women in poor households was high were more likely to believe that a woman has the right to refuse sex if her husband has an STI (p\.01). Finally, this belief was more likely among women living in Dhaka division compared to other divisions (p\ .001).
Discussion Using a nationally representative sample of a developing country, our results provide some of the first evidence of the influences of community-level poverty and women empowerment on married women’s safer sex negotiation attitudes. Strikingly, we found that higher community-level poverty was associated with greater positive safer sex negotiation attitudes for married women. This implies that there maybegreater needforsexual health promotion and prevention programs for married women in wealthier communities.
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Our findings revealed that the community-health link suggestedby previousliterature may operate in amore complex manner where women’s sexual health is concerned. Higher poverty in the community may contribute to weaken the norms of male dominance since husbands may struggle to perform their‘‘breadwinner’’ roles adequately (Banks, 2013). Similar to many other developing countries, families in Bangladesh are organized around rigid gender segregated roles where men are ‘‘powerful patriarchs who have full authority over the family including both wives and children,’’and ideal husbands or fathers are those‘‘who successfully play the instrumental roles of being the breadwinners and protectors of the family’’ (Jesmin & Seward, 2011, p. 8). However, in poor communities where marriage does not protect women much from financial insecurity they may feel they can refuse sex if their husbands have STIs with little concern for the consequences (Trail & Karney, 2012). When we controlled for individual-level characteristics, we found that living in communities where wife beating was permissible lowered women’s odds of justifying safer sex negotiation even when they knew that their husbands had STIs. This result was consistent with recent research on intimate partner violence (IPV) that found that women living in areas where wife beating is permissible were more likely to report experiencing physical or sexual violence perpetuated by their husbands (Linos, Slopen, Subramanian, Berkman, & Kawachi, 2013). If IPV is a norm in the community, women may not negotiate safer sex with husbands for fear of a violent reaction (El-Bassel, Gilbert, & Rajah, 2000). Exposure to IPV has been found to decrease women’s confidence in their ability to negotiate safer sex practices, such as condom use, with a partner (Swan & O’Connell, 2012). A considerable number of women in Bangladesh favor inequitable gender
Arch Sex Behav
norms (Sayem & Nury, 2013), some of which are often claimed to bereligiouslysanctionedbutdisadvantagethemfurther.Navedand Persson (2008) noted that Muslim women in Bangladesh traditionally tend to have less mobility and be less vocal about their rights compared to their non-Muslim counterparts. The cultural constructs of gender roles are deeply rooted in the structure of society, such as family, inheritance, and division of labor within the households. Similar to Bangladesh, in many other low-income countries, such as in Iran, women are expected to be sexually ignorant and are socialized to prioritize their husbands’ pleasure and negate their own sexual protection (Lotfi et al., 2013). Rigid genderrolesaresodeeplyrootedintheAfro-SurinameseandDutch Antillean communities in the Netherlands that wives in these communities are less likely to negotiate safer sex in fear of becominglessdesirabletotheirhusbands(Bertens,Krumeich,Borne, & Schaalma, 2008). We also found that women’s odds of positive safer sex negotiation attitudes were higher in neighborhoods where women tend tobeinvolvedinmajorhouseholddecisionsandinneighborhoods located in Dhaka division. Both of these characteristics represent environments with potentially greater opportunities for women. For example, women living in Dhaka division likely face fewer constraints to conform to gender norms due to their proximity to thecountry’scapitalcityanditsrelativelyprogressiveatmosphere (Jesmin & Cready, 2014). These women also likely benefit from the division’s formal sectoremployment options, especially in the garmentssector(United NationsConference onTrade and Development, 2012). For cash-income dependent households in the division, women’s employment in the formal sector represent both a‘‘necessary evil’’for survival and a‘‘strategy for advancement’’ (Banks, 2013, p. 99). Examining the effects of women’s employment on low-income household dynamics in Dhaka, Banks (2013) noted that while wives’ employment can lead to marital tensions and husbands’ negative behaviors, when ‘‘husbands do not behave in line with household interests’’ wives‘‘may vocally challenge their husbands because these behaviors reduce the impact that their additional labor has on the household’’ (p. 106). It seems reasonable that these dynamics could motivate married women to negotiate for safer sex. Several limitations of this study should be noted. First, since we used opinions on sexuality collected from self-reports of women in a conservative society, we cannot reject the possibility of social desirability response bias in the data (Meston, Heiman, Trapnell, & Paulhus, 1998). Second, the 600 ‘‘communities’’ (PSUs) in our study were administrative and small geographic units, which may or may not reflect functional communities or neighborhoods. Moreover, social cohesion and interaction are not necessarily bounded geographically (Diez Roux, 2001). Additionally, our study was cross-sectional. Longitudinal dimensions should be considered in future studies. For example,
living in a community that has been recently impoverished may not have same effect as living in a chronically impoverished community. Despite these limitations, our findings are generalizable to similar settings in developingcountriesbecause ofthe large and representative sample. Given that the burden of STIs is greatest in low-income countries and combating STIs is one of the core aspects of WHO’s Global Strategy on Reproductive Health (WHO, 2013), our findings have important public health policy implications. We recommend the development of STI awareness and prevention programs that target married women. While research on community influences calls for focusing on disadvantaged communities (e.g., Jesmin & Chaudhuri, 2013; Lindberg & Orr, 2011), our research highlights the importance of not underestimating the challenges that married women in economically privileged communities face in negotiating safer sex. Women in wealthier communities may have greater access to diagnosis and treatment; however, lack of safer sex negotiation power may put these women at higherriskofcontractingSTIsinthefirstplace.Ourstudyidentified two patterns that can inform sexual health promotion programs. First, community context matters. For example, program messages and strategies that acknowledge the influence of prevailing gender norms and women’s empowerment in the community are warranted. Mass media use, including the use of radio and television campaigns, has been shown to influence safer sex attitudes, norms, and practices (Farr, Witte, Jarato, & Menard, 2005) and, thus, is a promising strategy for changing gender norms and women’s empowerment in communities. Other strategies include empowering women through microfinance-based interventions. For example, Kim et al. (2007) tested such an intervention to reduce IPV in rural South Africa. They implemented Intervention with Microfinance for AIDS and Gender Equity (IMAGE), which combined participatory training in several areas, including domestic violence, HIV and sexuality, and gender roles, with a microfinance program. After 2 years, significant increases in women’s awareness and empowerment and significant decreases in IPV were observed in the intervention villages compared to the control villages. In summary, our results underscore the benefit of communitycontext specific intervention programs for STIs among married women. In the global effort to promote sexual and reproductive rights of women in low- and middle-income countries, WHO and the World Bank and many other international organizations have been collaborating with governments and local partners (WHO, 2012). Generation of knowledge to identify the most vulnerable groups of women is critical to design efficient programs. Sexual and reproductive health promotion programs targeted only to the poorest communities may not be sufficient. To have the greatest impact on women’s sexual and reproductive health, policies and programs need to be directed to women in wealthier communities as well.
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